normalized-cut segmentation using color and texture data

This code implemented a “normalized-cut” segmentation using color and texture information

This code segment an image using color, texture and spatial data
RGB color is used as an color data
Four texture features are used: 1. mean 2. variance 3. skewness 4. kurtosis
Normalized Cut (inherently uses spatial data)
ncut parameters are "SI" Color similarity, "ST" Texture similarity, "SX" Spatial similarity, "r" Spatial threshold (less than r pixels apart), "sNcut" The smallest Ncut value (threshold) to keep partitioning, and "sArea" The smallest size of area (threshold) to be accepted as a segment
an implementation by "Naotoshi Seo" with a small modification is used for “normalized-cut” segmentation, available online at: "http://note.sonots.com/SciSoftware/NcutImageSegmentation.html", It is sensitive in choosing parameters.